arXiv AI July 21, 2026 By Xiaohan Ye, Xu Chen, Zihan Gong, Jian Ding, Lianyu Du, Baicheng Chen, Yunmeng Shu, Jingqian Zhao, Zhixiang Zhao, Shuaiqi Jia, Chong Ma, Shuwen Xiao, Xiangheng Kong, Yuan Gao, Jun Song, Jinsong Lan, Xiaoyong Zhu, Bo Zheng

Pailitao-MMSearch: Building Native E-Commerce Multimodal Search Foundation

Read the original on arXiv AI →

arXiv:2607. 17499v1 Announce Type: new Abstract: The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex multimodal interactions that seamlessly combine product images, natural language descriptions, and mixed-intent instructions.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

Jul 14

MMRM: A Multiplex Multimodal Representation Model for Product Ranking in E-commerce Search

arXiv:2607. 11030v1 Announce Type: cross Abstract: Multimodal information is pivotal for e-commerce search ranking.

By Zhen-Lin Chen, Maosen Sheng, Peng Lin, Jianmin Chen, Zhuojian Xiao, Dongyue Wang, Xiwei Zhao

llms fine-tuning multimodal

arXiv AI

Aug 3

MMShopBench: A Real-Log Benchmark for Multimodal, Multi-Turn Shopping Agents

arXiv:2607. 29002v1 Announce Type: new Abstract: Online shoppers increasingly turn to AI shopping assistants, using images and multi-turn dialogue to express and refine product needs that are difficult to articulate in text alone.

By Zeying Hao, Hao Guo, Mengtao Xu, Yimin Hu, Yuheng Song, Zesheng Zhou, Jinsong Lan, Xiaoyong Zhu

agents fine-tuning multimodal benchmarks

arXiv Machine Learning

Aug 3

GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System

arXiv:2607. 29213v1 Announce Type: cross Abstract: Modern recommender systems in food delivery increasingly leverage multimodal signals, including images, text, and user interaction histories, to enhance user experience, yet effective fusion of these heterogeneous modalities remains challenging, hindering both the joint modeling of multimodal signals and adaptation to evolving user intent.

By Jiping Liu, Zhongmin Zhang, Zisen Sang, Zhijia Fang, Tao Ouyang, Ma Jiang, Shaopeng Liang, Zeyang Hou, Guodong Cao, Jia Jia

rag reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv AI

Jul 7

Enhancement of E-commerce Sponsored Search Relevancy with LLM

arXiv:2607. 03886v1 Announce Type: cross Abstract: Sponsored search plays a crucial role as a revenue stream for search engines, wherein advertisers competitively bid on keywords that align with the users' search queries.

By Md Omar Faruk Rokon, Andrei Simion, Weizhi Du, Musen Wen, Hong Yao, Kuang-chih Lee

llms fine-tuning safety

arXiv Machine Learning

Jul 31

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding

arXiv:2511. 12449v3 Announce Type: replace-cross Abstract: Recent Multimodal Large Language Models (MLLMs) have significantly advanced e-commerce product understanding.

By Zhanheng Nie, Chenghan Fu, Daoze Zhang, Junxian Wu, Wanxian Guan, Pengjie Wang, Jian Xu, Bo Zheng

llms multimodal benchmarks safety data-engineering

arXiv AI

Aug 6

MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding

arXiv:2604. 00513v3 Announce Type: replace-cross Abstract: With the rapid growth of e-commerce, exploring general representations rather than task-specific ones has attracted increasing attention.

By Junxian Wu, Chenghan Fu, Zhanheng Nie, Daoze Zhang, Bowen Wan, Wanxian Guan, Chuan Yu, Jian Xu, Bo Zheng

llms rag reinforcement-learning fine-tuning multimodal benchmarks

Related stories

MMRM: A Multiplex Multimodal Representation Model for Product Ranking in E-commerce Search

MMShopBench: A Real-Log Benchmark for Multimodal, Multi-Turn Shopping Agents

GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System

Enhancement of E-commerce Sponsored Search Relevancy with LLM

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding

MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding